When assembling a biological synthetic process, multiple alternatives typically exist for each of the operations and parts in the process, such as the structure and identity of the genetic constructs used, the particular protocol used to perform a step such as a transformation, purification etc. The question of how to design the most efficient process is therefore one of choosing a set of parts and operations, in order to satisfy design criteria such as maximising yield of the required output.
There are very large numbers of variables that influence the overall yield of product in a biological synthetic process, such as the host organism selected and the particular strain of host species used, physical factors such as temperature, pH and oxygen availability and timing of reactions, to name a few. Therefore, the choice of suitable parts and operations that make up a multi-step process has to be made in the context of a highly dimensional design space. Often the combination of variables that work in the context of one manufacturing facility cannot be easily transposed to other facilities. This leads to considerable difficulties in standardisation of bio-processing and represents a key challenge for the future of synthetic biology. By way of example, a 2012 report in Nature recounted that scientists at biotech company Amgen had only managed to reproduce around 11% of 53 published cancer-related studies which they had attempted over the previous years (Begley C. G & Ellis L. M., Nature 483, 531-533 (29 Mar. 2012). Similarly, the pharmaceutical company Bayer has indicated that in their estimation only 20-25% of published data corresponded to their own in-house findings (Prinz, F., Schlange, T. & Asadullah, K. Nature Rev. Drug Discov. 10, 712 (2011)).
Conventionally, essential process or experimental design decisions have to-date been made arbitrarily based on what is usual in the art, available or known to the experimenter or manufacturer at the time of setting up the process or experimental pipeline. Decisions in biological process design are often habitual or based upon artisanal know-how passed down within laboratories or industrial organisations. This is often complicated with time and resource constraints leading to a trial and error development in which a pipeline is adjusted by exchanging discrete parts and operations or modifying parameters, in order to improve the features of the starting pipeline. This results in design decisions that are often suboptimal or require substantial resources to identify reagents, operations and parameters that might be merely satisfactory. Hence, there can be considerable institutional resistance to change a process once it has been settled upon due to the inherent uncertainty associated with the optimization strategy as a whole.
Despite these problems many successful bioprocesses have been developed and there is a recognised potential for bio-based manufacturing to provide enormous benefits across many areas. Hence, there exists a need in the art—particularly within synthetic biology—to provide methods and systems that can facilitate the design of experimental or production pipelines from the level of the laboratory bench up to and including the industrial-scale bioreactor. In particular there is a need to provide methods and systems that can facilitate like-for-like comparisons between processes as well as standardised approaches for defining parts and protocols that may be used in experimental design, bioprocessing and manufacturing. To achieve this, there exists a need in the art to provide methods and systems that can facilitate reliable design of experiments from the level of the lab bench up to and including the industrial-scale bioreactor. These and other uses, features and advantages of the invention should be apparent to those skilled in the art from the teachings provided herein.